{"id":"https://openalex.org/W7213448917","doi":"https://doi.org/10.20944/preprints202609.0981.v2","title":"Dynamic LeJEPA: Maximum Entropy Representations for Sequential Prediction and Latent Planning with Theoretical Guarantees","display_name":"Dynamic LeJEPA: Maximum Entropy Representations for Sequential Prediction and Latent Planning with Theoretical Guarantees","publication_year":2026,"publication_date":"2026-09-16","ids":{"openalex":"https://openalex.org/W7213448917","doi":"https://doi.org/10.20944/preprints202609.0981.v2"},"language":"en","primary_location":{"id":"doi:10.20944/preprints202609.0981.v2","doi":"https://doi.org/10.20944/preprints202609.0981.v2","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202609.0981.v2","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.20944/preprints202609.0981.v2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128067423","display_name":"Mohsen Mostafa","orcid":"https://orcid.org/0009-0004-4478-0317","observed_orcids":["https://orcid.org/0009-0004-4478-0317"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mohsen Mostafa","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0004-4478-0317","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5128067423"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11883","display_name":"Embodied and Extended Cognition","score":0.003000000026077032,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/jepa","display_name":"JEPA","score":0.9120000004768372},{"id":"https://openalex.org/keywords/latent-world-models","display_name":"latent world models","score":0.9179999828338623},{"id":"https://openalex.org/keywords/cross-entropy-method","display_name":"cross-entropy method","score":0.765999972820282},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.6119999885559082},{"id":"https://openalex.org/keywords/sequence-prediction","display_name":"sequence prediction","score":0.4180000126361847}],"concepts":[{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.6592000126838684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5515999794006348},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5468999743461609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.513700008392334},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.44350001215934753},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43950000405311584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3758000135421753},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3538999855518341},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.30809998512268066},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C193856179","wikidata":"https://www.wikidata.org/wiki/Q5251100","display_name":"Defeasible estate","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.25859999656677246},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C80478641","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential analysis","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.20944/preprints202609.0981.v2","doi":"https://doi.org/10.20944/preprints202609.0981.v2","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202609.0981.v2","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.20944/preprints202609.0981.v2","doi":"https://doi.org/10.20944/preprints202609.0981.v2","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202609.0981.v2","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7172432896","https://openalex.org/W7212136613","https://openalex.org/W7201875857","https://openalex.org/W7160376401","https://openalex.org/W7171663849","https://openalex.org/W7203783470","https://openalex.org/W7202137576","https://openalex.org/W7160937895","https://openalex.org/W7214783055","https://openalex.org/W7203597620"],"abstract_inverted_index":{"Joint-Embedding":[0],"Predictive":[1],"Architectures":[2],"(JEPAs)":[3],"are":[4,122],"emerging":[5],"as":[6,382,415],"the":[7,44,107,113,118,145,199,238,255,272,284,306,332,337,346,355,360,366,387,416,423,436],"backbone":[8],"for":[9,296,327,429,461],"latent":[10,300,391,456],"world":[11,180,431],"models":[12,27,310],"in":[13,81,189],"robotics":[14,214],"and":[15,132,162,171,185,193,258,321,375,409],"autonomous":[16,160],"driving,":[17],"yet":[18],"inject-ing":[19],"domain":[20],"knowledge":[21],"(physics,":[22],"kinematics,":[23],"geometry)":[24],"into":[25],"these":[26],"consistently":[28,311],"degrades":[29],"performance\u2014with":[30],"no":[31,76],"theoretical":[32],"explanation.":[33],"We":[34,125,242,378],"resolve":[35],"this":[36,127,245,344,380],"para-dox":[37],"by":[38,68,399],"proving,":[39],"through":[40,136],"six":[41],"theorems,":[42],"that":[43,75,198,217,231,266,403],"isotropic":[45],"maximum-entropy":[46],"embedding":[47],"is":[48,237,335,397,422,440],"symmetry-stable":[49],"under":[50,62,166],"sequential":[51],"prediction":[52,66],"losses\u2014no":[53],"first-order":[54],"incentive":[55],"exists":[56],"to":[57,278,345],"rotate":[58],"away":[59,358],"from":[60,359],"it":[61,80,439],"any":[63],"Lipschitz,":[64],"Euclidean-invariant":[65],"objective\u2014and":[67],"validating":[69],"across":[70,129,159,318],"a":[71,85,90,137,168,172,194,248,261,299,352,383,394,404,447],"phased":[72,138],"empirical":[73],"protocol":[74,139],"non-Gaussian":[77],"alter-native":[78],"outperforms":[79,312],"practice.":[82],"This":[83],"yields":[84],"world-model":[86],"design":[87],"principle":[88],"with":[89,203,446],"provable":[91],"guarantee:":[92],"encoder":[93,134,170,176,251,323,376],"maximum-entropy,":[94],"predictor":[95],"dynamics,":[96],"decoder":[97,396],"physics\u2014and":[98],"explains":[99],"why":[100],"prior":[101],"physics-informed":[102,430],"JEPAs":[103],"failed:":[104],"they":[105,121],"constrained":[106],"encoder,":[108],"where":[109,120,435,443],"constraints":[110],"provably":[111,123],"destroy":[112],"entropy":[114,240],"guarantee,":[115],"instead":[116],"of":[117,178,354,372,463],"decoder,":[119],"benign.":[124],"validate":[126],"prin-ciple":[128],"two":[130,133],"domains":[131],"mechanisms":[135],"covering":[140],"measurement":[141],"artifacts":[142],"(Proposition":[143],"1:":[144],"N/K":[146],"\u2265":[147],"5":[148],"reliability":[149],"threshold),":[150],"pow-":[151],"ered":[152],"statistical":[153],"testing":[154],"(110":[155],"seeded":[156],"ablation":[157,319],"runs":[158],"driving":[161],"bimanual":[163],"robotic":[164],"manipulation,":[165],"both":[167,322],"SIGReg-regularized":[169],"marginal-only":[173,249],"VAE-KL":[174,250],"encoder\u2014the":[175],"family":[177],"classical":[179],"models\u2014with":[181],"paired":[182],"Wilcoxon":[183],"significance":[184],"joint":[186],"Holm":[187],"correction":[188],"every":[190],"domain\u00d7mechanism":[191],"combina-tion),":[192],"budget":[195],"replication":[196],"demonstrating":[197],"encoder-physics":[200],"violation":[201],"deepens":[202],"training.":[204],"Phase":[205,308],"3":[206,309],"additionally":[207],"characterizes":[208],"an":[209],"entropy\u2013utility":[210],"frontier":[211],"on":[212,228,254,305,315,386,452],"low-intrinsic-dimension":[213],"data,":[215,257],"discovering":[216,348],"per-dimension":[218],"variance":[219],"matching":[220],"alone":[221],"produces":[222],"correlated":[223],"collapse\u2014a":[224],"failure":[225,246],"mode":[226],"invisible":[227,277],"high-dimensional":[229],"data\u2014and":[230],"optimization":[232],"budget,":[233],"not":[234],"regularization":[235],"weight,":[236],"binding":[239],"constraint.":[241],"further":[243,292],"show":[244],"generalizes:":[247],"collapses":[252],"identically":[253],"same":[256],"we":[259,291,410],"introduce":[260],"posterior":[262],"signal-fraction":[263],"diagnostic":[264,342],"revealing":[265],"such":[267],"collapse":[268],"can":[269,458],"hide":[270],"beneath":[271],"encoder\u2019s":[273],"own":[274],"sampling-noise":[275],"floor,":[276],"marginal":[279],"diagnostics.":[280],"To":[281],"test":[282],"whether":[283],"placement":[285,374],"rule":[286],"matters":[287],"beyond":[288],"repre-sentation":[289],"quality,":[290],"probe":[293],"its":[294],"consequence":[295],"downstream":[297,407],"control:":[298],"cross-entropy-method":[301],"(CEM)":[302],"planner":[303,347],"built":[304],"trained":[307],"real-action":[313],"replay":[314],"model-internal":[316],"cost":[317],"conditions":[320],"mechanisms\u2014an":[324],"impossible":[325],"result":[326,421,451],"genuine":[328],"planning,":[329],"since":[330],"replaying":[331],"true":[333,361],"actions":[334],"itself":[336],"ground-truth":[338],"solution.":[339],"A":[340],"model-exploitation":[341],"traces":[343],"action":[349,356],"sequences":[350],"roughly":[351],"quarter":[353],"range":[357],"trajectory":[362],"while":[363],"still":[364],"lowering":[365],"learned":[367,395],"decoder\u2019s":[368],"cost,":[369],"uniformly":[370],"regardless":[371],"physics":[373,434],"choice.":[377],"report":[379],"transparently":[381],"boundary":[384],"condition":[385],"practical":[388],"claim:":[389],"offline":[390,455],"planning":[392,457],"against":[393],"not,":[398],"itself,":[400],"sufficient":[401],"evidence":[402,462],"representation":[405],"supports":[406],"control,":[408],"identify":[411],"closed-loop,":[412],"simulator-verified":[413],"execution":[414],"necessary":[417],"next":[418],"test.":[419],"The":[420],"first":[424],"formal,":[425],"cross-domain":[426],"validated":[427],"blueprint":[428],"models:":[432],"place":[433],"theorem":[437],"says":[438],"safe,":[441],"never":[442],"intuition":[444],"suggests\u2014together":[445],"concrete,":[448],"reproducible":[449],"cautionary":[450],"how":[453],"easily":[454],"be":[459],"mistaken":[460],"control":[464],"competence.":[465]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-09-17T00:00:00"}
